app.py

import os
import streamlit as st
import matplotlib.pyplot as plt
import pandas as pd
import requests

st.set_page_config(page_title="Miragic Sales Pilot", page_icon="📊")
st.title("📊 Miragic Sales Pilot")
sales_file = None
# st.write("Enter comma-separated numbers (e.g. `10, 20, 30`) to generate a bar chart.")

def upload_sales_data(data: pd.DataFrame):
    upload_url = os.environ['upload_url']

    files = {'file': data.to_csv(index=False)}
    response = requests.post(upload_url, files=files)
    return response.json()

def analyze_sales_data(sales_file: str, prompt: str):
    analyze_url = os.environ['analyze_url']
    
    data = {'filename': sales_file, 'question': prompt}
    response = requests.post(analyze_url, json=data)
    return response.json()

# Sidebar Menu
with st.sidebar:
    # TODO Name for product
    # st.title("📊 Miragic Sales Pilot")
    # st.subheader("Intelligent sales assistant")
    st.markdown("""
    ### 📝 Instructions
    1. **Upload your data**: Use the file uploader below to upload your sales data
    2. **File format**: Your file should be a CSV containing:
       - A 'Date' column
       - A 'Sales' column
    3. **Sample file**: Download our sample CSV below to see the expected format
    
    ### 🔍 What this app does
    - Analyzes your sales data
    - Generates visualizations
    - Provides intelligent insights
    
    ### ⚠️ Note
    Make sure your data is clean and follows the required format to get the best results.
    """)
    uploaded_file = st.file_uploader("", type=["csv", "excel"])
    if uploaded_file is not None:
      date_found = False
      sales_found = False
      df = pd.read_csv(uploaded_file, parse_dates=True)
      for column in df.columns:
        if 'Date' in column:  
          date_found = True
        if 'Sales' in column:
          sales_found = True
      if(date_found == False or sales_found == False):
        st.error('Please upload a csv containing both Date and Sales...')
        st.stop()

      response = upload_sales_data(df)
      sales_file = response['filename']

      st.success("File uploaded successfully!")
      st.write("Your uploaded data:")
      st.write(df)

    #   df = drop(df)
    #   df = date_format(df)
    #   merge_sort(df)
    #   series = group_to_three(df)

      st.session_state.uploaded = True

    with open(os.path.join(os.path.dirname(__file__), 'sample.csv'), 'rb') as f:
       st.download_button("Download our sample CSV", f, file_name='sample.csv')

    st.markdown("""![Visitors](https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FMiragic-AI%2FMiragic-Sales-Pilot&labelColor=%2337d67a&countColor=%23ff8a65&style=plastic&labelStyle=upper)""")

# Initialize chat history in session state
if "messages" not in st.session_state:
    st.session_state.messages = []

# Display chat history
for msg in st.session_state.messages:
    with st.chat_message(msg["role"]):
        if isinstance(msg["content"], str):
            st.markdown(msg["content"])
        else:
            st.pyplot(msg["content"])

# Chat input
prompt = st.chat_input("Top 10 selling products")
if prompt:
    # Add user message
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)

    response = analyze_sales_data(sales_file, prompt)

    dummy_response = response['result'][0]

    try:
        # Process input
        # values = list(map(int, prompt.strip().split(',')))
        # labels = [f"Item {i+1}" for i in range(len(values))]
        values = [item['y_axis'] for item in dummy_response['visualization']['data']]
        labels = [item['x_axis'] for item in dummy_response['visualization']['data']]

        # Create chart
        fig, ax = plt.subplots()
        ax.bar(labels, values, color="lightcoral")
        plt.xticks(rotation=45, ha='right')
        ax.set_title(dummy_response['visualization']['config']['title'])
        ax.set_ylabel(dummy_response['visualization']['config']['y_axis'])
        ax.set_xlabel(dummy_response['visualization']['config']['x_axis'])
        
        # Add value labels on top of each bar
        for i, v in enumerate(values):
            ax.text(i, v, f'{v:,.2f}', ha='center', va='bottom')

        # Generate analysis message
        analysis = "📊 Insights:\n"
        for insight in dummy_response['insights']:
          analysis += f"- {insight}\n"

        # Add bot replies
        st.session_state.messages.append({"role": "assistant", "content": fig})
        st.session_state.messages.append({"role": "assistant", "content": analysis})
        with st.chat_message("assistant"):
            st.pyplot(fig)
            st.markdown(analysis)

    except Exception as e:
        err_msg = f"❌ Error: {str(e)} — please enter only comma-separated numbers."
        st.session_state.messages.append({"role": "assistant", "content": err_msg})
        with st.chat_message("assistant"):
            st.markdown(err_msg)